The causal relationship between money supply, inflation and economic growth in vietnam

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE CAUSAL RELATIONSHIP BETWEEN MONEY SUPPLY, INFLATION AND ECONOMIC GROWTH IN VIETNAM BY NGUYỄN TRỌNG TÍN MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2013 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE CAUSAL RELATIONSHIP BETWEEN MONEY SUPPLY, INFLATION AND ECONOMIC GROWTH IN VIETNAM A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF ART IN DEVELOPMENT ECONOMICS By NGUYỄN TRỌNG TÍN Academic Supervisor: Assoc Prof Dr NGUYỄN VĂN NGÃI HO CHI MINH CITY, DECEMBER 2013 Declaration “This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Art in Development Economic to Vietnam - The Netherlands Programme I certify that the thesis has not already been submitted for any degree To the best of my knowledge, the thesis comprises only my original work All sources used have been cited and acknowledged in the thesis.” Nguyễn Trọng Tín i Acknowledgement I would like to express my deep gratitude to my academic supervisor, Assoc Prof Dr Nguyễn Văn Ngãi for his advices and helpful comments in this thesis My dearest thanks to Assoc Prof Dr Nguyễn Trọng Hoài and Dr Phạm Khánh Nam, who gave me many profound comments when this thesis was just in form of ideas My special thanks to Dr Nguyễn Hoàng Bảo and Dr Phùng Thanh Bình, I would not complete this thesis without their support in term of econometric techniques I would like to thank to all lecturers and staffs at the Vietnam – Netherlands Programme for their knowledge and patience during the period I studied at the program Finally, I would like to thank to my family, close friends, colleagues for their love and everything they gave me in life ii List of Abbreviations ADF Augmented Dickey-Fuller AIC Akaike’s Information Criterion AS-AD Aggregate Demand – Aggregate Supply model CPI Consumer Price Index ECT Error Correction Term GDP Gross Domestic Product GSO General Statistic Office HQ Hannan-Quinn information criterion IFS International Finance Statistic LR Likelihood ratio test M2 Broad money PP Phillips and Perron SIC Schwarz’s Information Criterion VECM Vector Error Correction Model iii Abstract This study analyzes the causal relationships between money supply, inflation and economic growth in Vietnam in the period of 1999Q2 – 2012Q3 Quarterly macroeconomic data were collected from IFS and GSO The thesis employs the Granger test in the Vector Error Correction Model (VECM) environment to find the Granger causal nexus of three variables for both in short run and long run There is one cointegration was found from Johansen’s test for cointegration The results show that there is a bidirectional relationship between economic growth and inflation for both in the short run and long run, and there are two unidirectional causalities from money supply to growth and inflation However, there is no evidence for the effectiveness of monetary policy in the short run Keywords: Johansen cointegration test, Granger causality, VECM, money supply, inflation, economic growth iv TABLE OF CONTENTS Declaration i Acknowledgement ii List of abbreviations iii Abstract iv Table of contents v List of tables viii List of figures ix CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objectives .4 1.3 Research questions 1.4 Scope of the study and methodology .5 1.5 Organization of the thesis CHAPTER 2: LITERATURE REVIEW 2.1 Theoretical literature 2.1.1 Theories about the Inflation – Economic growth relationship 2.1.2 Theories about the Inflation – Money supply relationship .9 2.1.3 Theories about the Money supply – Economic growth relationship 11 v 2.2 Empirical literature 14 2.3 Conceptual framework 17 CHAPTER 3: RESEARCH METHODOLOGY, MODEL SPECIFICATION AND DATA SOURCES 19 3.1 Analytical framework 20 3.2 Data sources 22 3.3 Model specification 22 3.4 Stationary and Unit root tests 24 3.5 Johansen’s test for Cointegration 26 3.6 Granger Causality Test 27 3.7 Impulse response functions 30 3.8 Variance decomposition 30 CHAPTER 4: FINDINGS AND DISCUSSION 31 4.1 An overview of inflation, money supply and economic growth in Vietnam from 1995 to 2012 31 4.1.1 Inflation 31 4.1.2 Money supply 34 4.1.3 Economic growth 37 4.2 Unit root testing 38 4.3 Estimation optimal lag for the model 40 4.4 Johansen cointegration test 40 4.5 Causality test for the long-run and short-run effect 45 vi 4.6 Comparing with previous studies 48 CHAPTER 5: CONCLUSIONS AND POLICY IMPLICATIONS 51 5.1 Conclusions 51 5.2 Policy implications 52 5.3 Limitation and Further studies 53 REFERENCES 54 APPENDIX 59 vii LIST OF TABLES Table 4.1: ADF and PP unit root tests on level time series 38 Table 4.2: ADF and PP unit root tests on first difference series 39 Table 4.3: Lag order selection of VAR (p) process 40 Table 4.4: Johansen’s cointegration test with lags 41 Table 4.5: Inflation equation in VECM model 42 Table 4.6: Money supply equation in VECM model 42 Table 4.7: Growth equation in VECM model 43 Table 4.8: Granger causality test base on VECM 44 Table 4.9: Variance decomposition 47 viii REFERENCES Abdullah, A Z., & Yusop, Z (1996) Money, Inflation and Causality: The Case of Malaysia (1970-92) The Asian Economic Review, 38(1), 44-51 Asteriou, D., & Hall, S G (2007) Applied Econometrics: a modern approach using eviews and microfit New York: Palgrave Macmillan Barro, R J (1995) Inflation and economic growth (No w5326) National Bureau of Economic Research Bernanke, B S., & Gertler, M (1995) Inside the black box: the credit channel of monetary policy transmission (No w5146) National Bureau of Economic Research Bui, D P.T (2011): “The effects of money growth on inflation in Vietnam from 2004 to 2010” Vietnam-Netherlands Programme for M.A 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5.52e-09 2.41e-09 9.99e-12 4.14e-12* 4.69e-12 5.31e-12 6.50e-12 0.175552 -10.50299 -11.33662 -16.83549 -17.74030* -17.65770 -17.59487 -17.48244 0.293647 -10.03061 -10.50995 -15.65454 -16.20507* -15.76818 -15.35107 -14.88436 0.219992 -10.32523 -11.02554 -16.39109 -17.16258* -16.94666 -16.75051 -16.50476 * indicates lag order selected by the criterion LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion 59 Appendix 2: Johansen cointegration test Date: 11/26/13 Time: 20:46 Sample: 54 Included observations: 49 Series: GROWTH LNCPI LNM2 Lags interval: to Selected (0.05 level*) Number of Cointegrating Relations by Model Data Trend: None None Linear Linear Quadratic No Test Type Intercept Intercept Intercept Intercept Intercept No Trend No Trend No Trend Trend Trend Trace 1 Max-Eig 1 *Critical values based on MacKinnon-Haug-Michelis (1999) Information Criteria by Rank and Model Data Trend: None None Linear Linear No Rank or Intercept Intercept Intercept Intercept No of CEs No Trend No Trend No Trend Trend Quadratic Intercept Trend Log Likelihood by Rank (rows) and Model (columns) 454.8073 454.8073 459.6234 459.6234 469.5929 467.3660 471.1440 475.5507 476.7427 480.2587 473.2261 477.9089 481.8433 484.7189 487.5473 474.2390 483.7522 483.7522 487.6499 487.6499 Akaike Information Criteria by Rank (rows) and Model (columns) -17.09418 -17.09418 -17.16830 -17.16830 -17.45277 -17.36188 -17.47527 -17.57350 -17.58134 -17.64321 -17.35617 -17.46567 -17.58544 -17.62118 -17.69581* -17.15261 -17.41846 -17.41846 -17.45510 -17.45510 Schwarz Criteria by Rank (rows) and Model (columns) -15.70427 -15.70427 -15.66257 -15.66257 -15.83121 -15.74032 -15.81510 -15.83611* -15.80534 -15.79000 -15.50296 -15.53524 -15.61640 -15.57492 -15.61095 -15.06775 -15.21777 -15.21777 -15.13858 -15.13858 60 Appendix 3: Vector Error Correction Estimates Vector Error Correction Estimates Date: 11/27/13 Time: 12:15 Sample (adjusted): 54 Included observations: 49 after adjustments Standard errors in ( ) & t-statistics in [ ] Cointegrating Eq: CointEq1 LNCPI(-1) 1.000000 LNM2(-1) -0.431159 (0.03537) [-12.1891] GROWTH(-1) -7.056420 (7.35880) [-0.95891] C 1.458701 Error Correction: D(LNCPI) D(LNM2) D(GROWTH) CointEq1 -0.069841 (0.01972) [-3.54162] -0.024474 (0.04380) [-0.55879] -0.024740 (0.01175) [-2.10508] D(LNCPI(-1)) 0.550027 (0.16871) [ 3.26020] 0.081486 (0.37470) [ 0.21747] -0.187057 (0.10055) [-1.86042] D(LNCPI(-2)) -0.060593 (0.19866) [-0.30501] -0.682706 (0.44121) [-1.54734] -0.051458 (0.11839) [-0.43464] D(LNCPI(-3)) -0.203900 (0.19263) [-1.05851] 0.781259 (0.42782) [ 1.82613] -0.130241 (0.11480) [-1.13450] D(LNCPI(-4)) 0.050090 (0.13816) [ 0.36257] -0.321450 (0.30684) [-1.04762] 0.083226 (0.08234) [ 1.01080] D(LNM2(-1)) -0.131542 (0.08290) [-1.58679] 0.759739 (0.18411) [ 4.12646] -0.060792 (0.04940) [-1.23050] D(LNM2(-2)) 0.180141 -0.733170 -0.034805 61 (0.09311) [ 1.93474] (0.20679) [-3.54546] (0.05549) [-0.62723] D(LNM2(-3)) -0.027470 (0.05872) [-0.46784] 0.325212 (0.13041) [ 2.49384] -0.003418 (0.03499) [-0.09767] D(LNM2(-4)) 0.100593 (0.05098) [ 1.97302] -0.055591 (0.11323) [-0.49093] 0.022821 (0.03038) [ 0.75105] D(GROWTH(-1)) -0.643154 (0.32302) [-1.99108] -0.169388 (0.71741) [-0.23611] -1.473605 (0.19251) [-7.65476] D(GROWTH(-2)) -0.483212 (0.29992) [-1.61115] -0.142992 (0.66611) [-0.21467] -1.449226 (0.17874) [-8.10796] D(GROWTH(-3)) -0.343503 (0.28548) [-1.20325] -0.138134 (0.63404) [-0.21786] -1.430917 (0.17014) [-8.41037] D(GROWTH(-4)) -0.275048 (0.27474) [-1.00112] -0.042562 (0.61019) [-0.06975] -0.363777 (0.16374) [-2.22172] C 0.008656 (0.00850) [ 1.01863] 0.045145 (0.01887) [ 2.39205] 0.012176 (0.00506) [ 2.40425] 0.806970 0.735272 0.004160 0.010902 11.25527 160.1388 -5.964850 -5.424329 0.020152 0.021188 0.550742 0.383874 0.020518 0.024212 3.300476 121.0395 -4.368961 -3.828441 0.059769 0.030846 0.999863 0.999812 0.001477 0.006497 19663.14 185.4996 -6.999985 -6.459465 -0.007223 0.474157 R-squared Adj R-squared Sum sq resids S.E equation F-statistic Log likelihood Akaike AIC Schwarz SC Mean dependent S.D dependent Determinant resid covariance (dof adj.) 2.05E-12 Determinant resid covariance 7.46E-13 Log likelihood 475.5507 Akaike information criterion -17.57350 Schwarz criterion -15.83611 62 Appendix 4: Inflation equation in VECM model Dependent Variable: D(LNCPI) Method: Least Squares Date: 11/27/13 Time: 12:23 Sample (adjusted): 54 Included observations: 49 after adjustments D(LNCPI) = C(1)*( LNCPI(-1) - 0.431158887994*LNM2(-1) 7.05642021657*GROWTH(-1) + 1.45870102328 ) + C(2)*D(LNCPI(-1)) + C(3)*D(LNCPI(-2)) + C(4)*D(LNCPI(-3)) + C(5)*D(LNCPI(-4)) + C(6) *D(LNM2(-1)) + C(7)*D(LNM2(-2)) + C(8)*D(LNM2(-3)) + C(9)*D(LNM2( -4)) + C(10)*D(GROWTH(-1)) + C(11)*D(GROWTH(-2)) + C(12) *D(GROWTH(-3)) + C(13)*D(GROWTH(-4)) + C(14) Coefficient Std Error t-Statistic C(1) C(2) C(3) C(4) C(5) C(6) C(7) C(8) C(9) C(10) C(11) C(12) C(13) C(14) -0.069841 0.550027 -0.060593 -0.203900 0.050090 -0.131542 0.180141 -0.027470 0.100593 -0.643154 -0.483212 -0.343503 -0.275048 0.008656 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.806970 0.735272 0.010902 0.004160 160.1388 11.25527 0.000000 0.019720 0.168710 0.198658 0.192629 0.138155 0.082898 0.093109 0.058716 0.050984 0.323018 0.299917 0.285480 0.274741 0.008498 -3.541622 3.260200 -0.305010 -1.058513 0.362565 -1.586791 1.934745 -0.467842 1.973022 -1.991080 -1.611153 -1.203246 -1.001118 1.018625 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 63 Prob 0.0011 0.0025 0.7622 0.2971 0.7191 0.1216 0.0611 0.6428 0.0564 0.0543 0.1161 0.2370 0.3236 0.3154 0.020152 0.021188 -5.964850 -5.424329 -5.759777 1.637705 Appendix 5: Money supply equation in VECM model Dependent Variable: D(LNM2) Method: Least Squares Date: 11/27/13 Time: 12:24 Sample (adjusted): 54 Included observations: 49 after adjustments D(LNM2) = C(15)*( LNCPI(-1) - 0.431158887994*LNM2(-1) 7.05642021657*GROWTH(-1) + 1.45870102328 ) + C(16)*D(LNCPI( -1)) + C(17)*D(LNCPI(-2)) + C(18)*D(LNCPI(-3)) + C(19)*D(LNCPI(-4)) + C(20)*D(LNM2(-1)) + C(21)*D(LNM2(-2)) + C(22)*D(LNM2(-3)) + C(23)*D(LNM2(-4)) + C(24)*D(GROWTH(-1)) + C(25)*D(GROWTH(-2)) + C(26)*D(GROWTH(-3)) + C(27)*D(GROWTH(-4)) + C(28) Coefficient Std Error t-Statistic C(15) C(16) C(17) C(18) C(19) C(20) C(21) C(22) C(23) C(24) C(25) C(26) C(27) C(28) R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) -0.024474 0.081486 -0.682706 0.781259 -0.321450 0.759739 -0.733170 0.325212 -0.055591 -0.169388 -0.142992 -0.138134 -0.042562 0.045145 0.550742 0.383874 0.024212 0.020518 121.0395 3.300476 0.002420 0.043797 0.374699 0.441214 0.427823 0.306838 0.184114 0.206792 0.130406 0.113235 0.717413 0.666107 0.634043 0.610191 0.018873 -0.558793 0.217472 -1.547337 1.826128 -1.047621 4.126455 -3.545455 2.493844 -0.490933 -0.236109 -0.214668 -0.217862 -0.069752 2.392045 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 64 Prob 0.5799 0.8291 0.1308 0.0764 0.3020 0.0002 0.0011 0.0175 0.6265 0.8147 0.8313 0.8288 0.9448 0.0223 0.059769 0.030846 -4.368961 -3.828441 -4.163888 1.928925 Appendix 6: Growth equation in VECM model Dependent Variable: D(GROWTH) Method: Least Squares Date: 11/27/13 Time: 12:25 Sample (adjusted): 54 Included observations: 49 after adjustments D(GROWTH) = C(29)*( LNCPI(-1) - 0.431158887994*LNM2(-1) 7.05642021657*GROWTH(-1) + 1.45870102328 ) + C(30)*D(LNCPI( -1)) + C(31)*D(LNCPI(-2)) + C(32)*D(LNCPI(-3)) + C(33)*D(LNCPI(-4)) + C(34)*D(LNM2(-1)) + C(35)*D(LNM2(-2)) + C(36)*D(LNM2(-3)) + C(37)*D(LNM2(-4)) + C(38)*D(GROWTH(-1)) + C(39)*D(GROWTH(-2)) + C(40)*D(GROWTH(-3)) + C(41)*D(GROWTH(-4)) + C(42) Coefficient Std Error t-Statistic C(29) C(30) C(31) C(32) C(33) C(34) C(35) C(36) C(37) C(38) C(39) C(40) C(41) C(42) R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) -0.024740 -0.187057 -0.051458 -0.130241 0.083226 -0.060792 -0.034805 -0.003418 0.022821 -1.473605 -1.449226 -1.430917 -0.363777 0.012176 0.011752 0.100546 0.118394 0.114801 0.082336 0.049405 0.055490 0.034993 0.030385 0.192508 0.178741 0.170137 0.163737 0.005064 0.999863 0.999812 0.006497 0.001477 185.4996 19663.14 0.000000 -2.105076 -1.860422 -0.434638 -1.134498 1.010803 -1.230499 -0.627235 -0.097667 0.751052 -7.654762 -8.107965 -8.410373 -2.221716 2.404254 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 65 Prob 0.0425 0.0712 0.6665 0.2643 0.3190 0.2267 0.5346 0.9228 0.4576 0.0000 0.0000 0.0000 0.0329 0.0216 -0.007223 0.474157 -6.999985 -6.459465 -6.794913 2.087720 Appendix 7: VEC Granger Causality/Block Exogeneity Wald Tests VEC Granger Causality/Block Exogeneity Wald Tests Date: 11/26/13 Time: 20:56 Sample: 54 Included observations: 49 Dependent variable: D(GROWTH) Excluded Chi-sq df Prob D(LNCPI) D(LNM2) 19.85389 1.621918 4 0.0005 0.8048 All 23.88853 0.0024 Dependent variable: D(LNCPI) Excluded Chi-sq df Prob D(GROWTH) D(LNM2) 30.82912 7.718190 4 0.0000 0.1025 All 40.89568 0.0000 Dependent variable: D(LNM2) Excluded Chi-sq df Prob D(GROWTH) D(LNCPI) 7.122175 5.221820 4 0.1296 0.2653 All 18.49413 0.0178 66 Appendix 8: Impulse response to Cholesky Period Period Period Response of LNCPI: LNCPI GROWTH 0.010902 0.017596 0.017668 0.012406 0.004776 -0.001450 -0.004707 -0.005495 0.000000 -0.000776 -9.50E-05 0.000505 0.001044 0.001795 0.002794 0.003716 Response of GROWTH: LNCPI GROWTH -0.002167 -0.001101 -0.001302 -0.001506 -0.001570 -5.70E-05 -4.80E-05 -0.000648 0.006125 -0.001760 0.000929 -0.000293 0.006436 -0.001947 0.000857 -0.000472 Response of LNM2: LNCPI GROWTH -0.011178 -0.019175 -0.024645 -0.023358 -0.019902 -0.019256 -0.020395 -0.021277 -0.001432 -0.002514 -0.002202 -0.001086 -0.001185 -0.001428 -0.001136 -0.001118 LNM2 0.000000 -0.002174 -0.000224 0.004729 0.010016 0.012875 0.012943 0.011513 LNM2 0.000000 -0.001074 -0.000563 -0.000203 0.000342 -0.002290 -0.001693 -0.000515 LNM2 0.021430 0.037937 0.035039 0.029692 0.029483 0.030611 0.029819 0.029102 Cholesky Ordering: LNCPI GROWTH LNM2 67 Appendix 9: Variance Decomposition Period Variance Decomposition of LNCPI: S.E LNCPI GROWTH LNM2 0.010902 0.020828 0.027313 0.030374 0.032354 0.034898 0.037621 0.039899 100.0000 98.77225 99.27813 96.96462 87.63624 75.49793 66.52942 61.04748 0.000000 0.138646 0.081828 0.093761 0.186849 0.425110 0.917320 1.682843 0.000000 1.089104 0.640043 2.941623 12.17691 24.07696 32.55326 37.26968 Variance Decomposition of GROWTH: Period S.E LNCPI GROWTH LNM2 Period 0.006497 0.006905 0.007110 0.007276 0.009846 0.010295 0.010469 0.010512 11.12813 12.39371 15.04106 18.64470 12.72430 11.64226 11.26162 11.54879 88.87187 85.18599 82.04889 78.49919 85.59562 81.87181 79.85015 79.39563 0.000000 2.420300 2.910055 2.856108 1.680086 6.485927 8.888229 9.055571 Variance Decomposition of LNM2: S.E LNCPI GROWTH LNM2 0.024212 0.048984 0.065110 0.075284 0.083273 0.090798 0.097728 0.104171 21.31534 20.53124 25.94751 29.03435 29.44257 29.26225 29.61484 30.23631 0.349685 0.348924 0.311867 0.254091 0.227931 0.216465 0.200371 0.187868 78.33498 79.11984 73.74063 70.71156 70.32950 70.52129 70.18479 69.57583 Cholesky Ordering: LNCPI GROWTH LNM2 68 ... 4.6: The causal relationship between inflation, money supply and economic growth in the short-run 45 Figure 4.7: The causal relationship between inflation, money supply and economic growth. .. indicate a causal relationship between these variables Recently, in Vo (2013), the author investigated the causal relationship between money supply, inflation and economic growth in Vietnam The. .. increase in LRAS and AD, leading to an increase in economic growth without inflation In general, the Keynesian theory points out the positive link between inflation and growth That is, when growth increases,